Head-to-Head Model Comparison

GPT-5 mini vs GPT-5 nano

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial

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GPT-5 miniProfile

GPT-5 nanoProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

GPT-5 mini

Modelo Leve e Econômico

O GPT-5 mini da OpenAI é um modelo de IA projetado para máxima economia por token e alto desempenho em escala de produção, oferecendo janela de contexto de 400K, velocidade de 185 tokens/s, índice de inteligência de 46/100 e tarifa de $0.25

Intelligence Index46 / 100

Input Token:

$0.25 / 1M

Output Token:

$2.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

52%

OpenAI

GPT-5 nano

Modelo Leve e Econômico

O GPT-5 nano da OpenAI é um modelo de IA projetado para máxima economia por token e alto desempenho em escala de produção, oferecendo janela de contexto de 400K, velocidade de 250 tokens/s, índice de inteligência de 35/100 e tarifa de $0.05

Intelligence Index35 / 100

Input Token:

$0.05 / 1M

Output Token:

$0.40 / 1M

Context Window:

400K tokens

SWE-bench Verified:

34.5%

Principais Diferenças em Resumo

GPT-5 nano is 5.0x cheaper for API usage (input + output tokens combined).
GPT-5 nano is faster at 250 tok/s vs 185 tok/s.
GPT-5 mini leads on SWE-bench coding (52.0% vs 34.5%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	GPT-5 mini	GPT-5 nano
Intelligence Index Composite reasoning & knowledge score (0-100)	46	35
Provider	OpenAI	OpenAI
Input Price Cost per million input tokens	$0.25 / 1M	$0.05 / 1M
Output Price Cost per million output tokens	$2.00 / 1M	$0.40 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.27 / 1M	$0.05 / 1M
Context Window Maximum input + output tokens	400K tokens~600 A4 pages of text	400K tokens~600 A4 pages of text
Max Output Tokens Per single request	128K	128K
Throughput Speed Tokens generated per second	185 tok/s	250 tok/s
SWE-bench Verified Real-world software engineering	52%	34.5%
GPQA Diamond Graduate-level reasoning	66%	48%
Cached Input Price Prompt caching discount per 1M tokens	$0.03 / 1M	$0.01 / 1M

Quem vence em cada categoria?

At-a-glance decision framework

Coding

GPT-5 mini

+17.5% SWE-bench lead

Cost

GPT-5 nano

5.0x cheaper monthly runtime

Speed

GPT-5 nano

+35% faster generation

Context

Tied

400K tokens window

Pontuações de Benchmarks Verificadas

Official evaluation metrics verified by independent third-party research labs.

GPT-5 miniGPT-5 nano

SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

52%vs34.5%

GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

66%vs48%

MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

78.5%vs66.5%

LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1315ptsvs1250pts

Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

9.2%vs6%

Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

30.5%vs18.5%

SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

32%vs22%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

56.5%vs37.5%

AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

84%vs62%

Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

68.5%vs57%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

185 tok/s vs250 tok/s

Latência e Tempo de Resposta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better

GPT-5 mini0.70s

GPT-5 nano0.38s

Est. End-to-End Response (500 tokens)TTFT + generation time

GPT-5 mini3.40s

GPT-5 nano2.38s

Simulador Interativo de Custo de Tokens

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

GPT-5 mini Monthly API Bill

$2.21 / month

$0.25/1M in · $2/1M out

GPT-5 nano Monthly API Bill

$0.44 / month

$0.05/1M in · $0.4/1M out

GPT-5 nano saves approximately $1.77 / month (80%) under this workload.5.0x Savings

GPT-5 mini · Strengths & Key Advantages

Janela de contexto de 400K com limite máximo de saída de 128K tokens (SWE-bench Verified 52% · GPQA Diamond 66%)
Taxa de transferência rápida de 185 tokens/segundo com latência inicial (TTFT) de 700 ms
Economia de API competitiva ($0.25/$2 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas

Considerations & Trade-offs

Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

GPT-5 nano · Strengths & Key Advantages

Janela de contexto de 400K com limite máximo de saída de 128K tokens (SWE-bench Verified 34.5% · GPQA Diamond 48%)
Taxa de transferência rápida de 250 tokens/segundo com latência inicial (TTFT) de 380 ms
Economia de API competitiva ($0.05/$0.4 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas

Considerations & Trade-offs

Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

Metric	GPT-5 mini	GPT-5 nano
Cost per Task Estimated USD to finish one task	$0.32	$0.06
Output Tokens / Task Tokens generated per task	50K	42K
Reasoning Tokens / Task Thinking tokens burned per task	24K	18K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	GPT-5 mini	GPT-5 nano
Official API Model ID (SDK)	gpt-5-mini	gpt-5-nano
API Protocol	OpenAI Responses API & Chat Completions v1	OpenAI Responses API & Chat Completions v1
Release Date	2025-08	2025-08
Knowledge Cutoff	September 2024	September 2024
Architecture	Compact unified reasoning model	Nano unified reasoning model
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($0.25/1M in) across full 400K window	Flat rate ($0.05/1M in) across full 400K window
Prompt Cache Policy & TTL	Automatic prefix caching at $0.025/1M (no extra cache-write fee)	Automatic prefix caching at $0.005/1M (no extra cache-write fee)
Computer Use / GUI Agent	Supported (Screen coordinate grounding, browser & desktop GUI action loops)	Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool Calling	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Sandbox	Native Web Search tool + Hosted Code Interpreter & File Search RAG	Native Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning Support	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAM	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier Classification	OpenAI Preparedness Framework Audited & System Card Published	OpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text, vision	text, vision
Output Modalities	text	text

GPT-5 mini vs GPT-5 nano: Respostas Rápidas (FAQ)

Which is more intelligent, GPT-5 mini or GPT-5 nano?

GPT-5 mini is more intelligent. It scores 46 compared with 35 on the composite Intelligence Index.

Which model is faster?

GPT-5 nano is faster, generating 250 tokens per second compared with 185 tokens per second.

Which model is cheaper to run?

GPT-5 nano is cheaper at $0.05 per 1M tokens blended, compared with $0.27 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-5 nano has lower latency, with a time to first token of 0.38s compared with 0.70s.

Veredito

Tanto GPT-5 mini (Indicado para máxima economia por token e alto desempenho em escala de produção, arquiteturas RAG corporativas e integração escalável via API.) quanto GPT-5 nano (Indicado para máxima economia por token e alto desempenho em escala de produção, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: GPT-5 mini lidera em inteligência geral e programação, GPT-5 nano oferece geração mais rápida e GPT-5 nano apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, GPT-5 mini ou GPT-5 nano?+

Nas avaliações de inteligência e código, GPT-5 mini leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, GPT-5 mini ou GPT-5 nano?+

O GPT-5 mini custa $0.25 / $2.00 por 1M de tokens (entrada/saída) e o GPT-5 nano custa $0.05 / $0.40. No custo combinado, GPT-5 nano é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O GPT-5 mini suporta 400K tokens de contexto contra 400K tokens do GPT-5 nano, enquanto GPT-5 nano entrega maior velocidade de geração.

AI Terminology & Guide

Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

GPT-5 mini vs GPT-5 nano

Troque e Compare Qualquer Modelo

GPT-5 mini

GPT-5 nano

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

GPT-5 mini · Strengths & Key Advantages

Considerations & Trade-offs

GPT-5 nano · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

GPT-5 mini vs GPT-5 nano: Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

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